Resumable Batch Protocol (RBP)

Checkpointing in batch processing records completed items to a JSON progress log after each chunk is processed. When the script restarts, it reloads this state and skips already finished items, ensuring progress is never lost even if the run is interrupted.

Idempotent batch processing ensures re-running a script skips completed items and yields the exact same results. It achieves this by tracking finished items in a JSON progress log, making long-running data processing tasks safe to re-execute after any interruption without duplicating work.

Idempotent re-execution for data migration tracks completed items in a JSON progress log and skips them on subsequent runs. This guarantees that re-running an interrupted migration yields the same results without duplicating records or wasting processing quotas.

Checkpointing prevents wasted AI quotas by processing data in small chunks and persisting completed IDs to a JSON progress log after each step. If a long-running task is interrupted, the system reloads its state and resumes, avoiding the need to reprocess finished items.

Idempotent checkpointing is needed for batch processing, data migration, and long-running tasks where interruptions can occur. It ensures that if a process fails mid-run, it can safely resume by skipping completed items tracked in a JSON progress log, preventing data loss and duplicate processing.

Resumable batch processing works with Python data migration scripts by chunking data into small, auditable steps and tracking completed items in a JSON progress log. This allows the script to reload state on startup and skip finished items, ensuring idempotent re-execution without data loss.